Another take on my perennial favourite social convention, the dress code: Signalling (on Cosmic Variance).

This instance of the pro-dress-code argument is so lame I can hardly be bothered to discuss it (“Everyone should dress so that they wouldn’t embarrass my mother”), but I welcome people making good fun out of it. So, like I already said back in the day, dressing up is about signalling status – but why do we have to drag aesthetics into this? Can’t we simply wear t-shirts that show our current bank balance, grade average, or pictures of our model-grade SOs? Why the silken suicide utility? I might add that signalling status is actually counterproductive in academia, since discussions are not supposed to be guided by “the guy with the necktie said it, so it must be true”-type decisions. In the long run, I hope that the belief in suit == authority will fade away, helped along by the tireless work of Chinese tailors flooding the market with cheap high quality evening dress. Still, I’m not holding my breath (nor am I as religious about the “don’t dress to impress” rule in real life, being the unprincipled cynic that I am).

Interesting:

The dangers of living in a zero-sum world economy
By Martin Wolf

We live in a positive-sum world economy and have done so for about two centuries. This, I believe, is why democracy has become a political norm, empires have largely vanished, legal slavery and serfdom have disappeared and measures of well-being have risen almost everywhere. What then do I mean by a positive-sum economy? It is one in which everybody can become better off. It is one in which real incomes per head are able to rise indefinitely.

The (filtered, and thus really good) comments have all kinds of views on the issue, from outright doomsayers to optimists who don’t see the current situation as all that different from past environmental crises. Personally, the idea scares me because it sounds plausible. Of course, there are plenty of open questions. I’d like to have a model that gives democracy as the optimal form of organization in the alleged positive-sum world and a different result in a negative sum world, for starters. Then, I’m not convinced that an energy shortage is actually enough to push our current equilibrium into a zero/negative-sum state. I wish I was an economics grad student with time to waste.

Via MR:

Scientific American: The Secret to Raising Smart Kids

Hint: Don’t tell your kids that they are. More than three decades of research shows that a focus on effort—not on intelligence or ability—is key to success in school and in life

Well, yes. This appears to be a good strategy since working hard will mostly improve your outcomes, whatever your innate abilities are (but note that the article doesn’t consider the existence or relative importance of innate abilities).

Me? I’m pretty much a fixed mindset person. I wouldn’t blame my parents (though I was told that I’m smart a lot), but rather the entire system of education that I’ve been slaving in for most of my life – it’s geared towards perfectly doing easy things instead of honorable failure on hard things, probably because it’s much easier to measure correctness of results than quality of effort. This breeds the habit that every problem is solvable, and if it seems hard, you’re doing something wrong (which is threatening, because failure on one of the semi-trivial school problems is a good indicator you’ll never amount to anything in real life).

Also, I’m wary of glorifying effort – stupidly slaving away on a tedious path to a solution is definitely not more praiseworthy than lazily inventing a brillant shortcut. An environment that rewards effort may well encourage pointless displays of busywork instead of much-needed contemplation. I’d feel stupid congratulating my (hypothetical) smart child for the hard work that both of us know wasn’t necessary to earn their grades in school. To actually keep them from falling into smug superiority, I’d try to expose them to enough of the past human greatness to emphasize the point that merely being the smartest kid in your class doesn’t amount to much.

On a related note, here’s David Friedman on home unschooling his kids, which sounds pretty reasonable to me.

Last week, Marginal Revolution linked to a paper by Diego Gambetta and Steffen Hertog, titled “Engineers of Jihad”.

When Tyler Cowen calls something “probably the best piece on terrorism I have read”, it definitely piques my interest. I finally managed to read its 90 pages today, and though I’m not in a position to judge a sociology paper as a peer, I’m impressed. The most directly interesting piece of analysis was the fact that engineers are much more likely to have a world view that is both conservative and religious than other disciplines. This appears to hold throughout the world, though it seems that the specific environment faced by engineers in NAME countries contributes to their overrepresentation among Islamic terrorists.

Their explanation of the fit between “the engineering mindset” and certain types of extremism is borrowed from an older book by Seymour Lipset and Earl Raab, which is actually about American right wing extremism, but the general features are a great fit for Islamic fanaticism:

• Monism, “the tendency to treat cleavage and ambivalence as illegitimate (…) the repression of difference and dissent, the closing down of the market place of
  ideas”
• Simplism, “unambiguous ascription of single causes and remedies for multifactored phenomena”
• Preservatism “aims to restore a lost, often mythical order of privilege and authority and, in the authors’ view, emerges as a backlash against displacement or status deprivation in a period of sharp social change”

Note also that unsuccessful engineers are more likely to have conservative/religious views than more successful ones, which fits pretty well with the authors’ view about the third point. How about this part?

In her detailed ethnography, Nilufer Göle found evidence of the above ideological features among Islamist engineers in Turkey: she shows that they entertain a strong belief in the superiority of logical and technical approaches towards societal issues, and see themselves as problem solvers, as “social engineers”, superior to the Kemalist elite of jurists preoccupied with debates on abstract ideas (1990: 172f.). They assume to know the “one best way” of improving society, and feel therefore entitled to speak in the interests of all (Göle 1990: 174). According to Olivier Roy, Islamist intellectuals, many of whom he says have a technical or scientific education, criticize the “messy” Western social sciences because they challenge the unity and divine order of the world, while, by contrast, the sciences, pure and applied, reflect the “the coherence of the whole, the rationality of the one [God]” (Roy 1992: 271; Hanafi 1997: 148).53 In line with “simplism”, modern radical Islamism often has little truck with the nuance and ambiguity of established Islamic theology (Roy 1990, 2004).54 When Bernard Haykel asked the engineers and scientists among the numerous fundamentalist Islamists he interviewed what it was about Salafi thought that appealed to them, they pointed to its intellectually clean, unambiguous and all-encompassing nature (personal communication, September 2007).

Ah yes. People seriously need to study the history of the twentieth century if they still believe that there is one great system that would sort out the whole mess of civilization, and which is prevented from coming about because the Evil Few [tm] benefit from the current order. We’ve been through this from two different angles already, and it should be apparent that the next One True Idea[tm] is going to fail in the same way.

Why would engineers be more susceptible to this view than, say, scientists? I suspect that it has to do with the nature of engineering education. Science, from an engineer’s view, is something that works and can be depended on. For the actual scientist, the established body of science has to be taken into account, but all the actual work is not about applying well known principles, but rather about poking holes into them and extending the frontiers. This is a much more disorderly process. In physics, for example, the student is treated to the regulated world of classical mechanics, just to have it overthrown in two mutually incompatible ways afterwards, and then left to slowly puzzle it together in elaborate and complicated ways. The central message is “damn, this is all very complex, and though we do know a lot, there’s even more we don’t”. I doubt that this is a major component of most engineering courses, particularly in an environment where engineering studies are seen as a qualification to the social elite.

What would I suggest to counteract this? I don’t have a recipe, but personally, I’m just too awed by the enormous complexity of our society to entertain the idea that I would know how to revolutionize it into something better. I think most people who think that they can change the world don’t really appreciate the awesome complexity and cooperation that go into simple acts of daily life – like your web browsing right now. Maybe a little more emphasis and embrace of all the awesome complexity that is around us – the turmoil of atoms, evolution, markets and democracy – would lead to less simple-minded radicalism?

Just to keep the flames down, I guess that computer science, though it aspires to produce an engineering branch, has not yet reached the maturity to actually have the effect that I ascribe to typical engineering subjects since the body of knowledge is too young and too rapidly changing to qualify.

Please note that I’ve known plenty of fine people in engineering, but the effects that the study finds on a large sample are rather significant and need an explanation. I’m speculating on that rather than trying to insult you.

The ever-interesting Edge has a fun new question/art project: WHAT IS YOUR FORMULA? YOUR EQUATION? YOUR ALGORITHM?

I wouldn’t really claim any equation as my own, but many of the existing entries seem to take the question more in the spirit of “your favourite…”. Since I’ve just had the opportunity to dig through an electrodynamics script that contains a puny 1111 numbered formulas (not counting letter-indexed sub-equations and the appendices), I have a couple of favourites to share, too. For sheer disgusting unintuitiveness, I propose this simple identity, which you can get from the continuity equation using just a few elementary transformations:

And for most awe-inspiring tensor trickery, this:

Ah, I’m almost sad that my life no longer revolves around electrodynamics. Note, however, that the stories of rainbows, a pony and eternal happiness after you pass the exam are greatly exaggerated. In reality, next week’s quantum theory problems and a growing realization of the festering heap of problems that were pushed aside for a month now is pretty much all you get. But at least there is the feeling that it’s an utterly natural thing to write a vector field as the divergence of its tensor product with the position vector if it satisfies natural boundary conditions. I guess that is something.

Pet peeve, as triggered by the Financial Times, here:

How computers routed the experts

By Ian Ayres

[...]

In Freakonomics, Steven D. Levitt and Stephen J. Dubner showed dozens of examples of how statistical analysis of databases can reveal the secret levers of causation. Yet Freakonomics didn’t talk much about the extent to which quick quantitative analysis of massive datasets – call it “super crunching” – is affecting real-world decisions. In fact, decision-makers in business and government are using statistical analysis to drive a wide variety of choices – and shunning the advice of traditional experts along the way.

Instead of simply throwing away the know-how of experts, wouldn’t it be better to combine super crunching and experiential knowledge? Can’t the two types of knowledge peacefully coexist? There is some evidence to support this possibility. Indeed, traditional experts are shown to make better decisions when they are provided with the results of statistical prediction.
But evidence is mounting in favour of a different and much more dehumanising mechanism for combining human and super-crunching expertise. Several studies have shown that the most accurate way to exploit traditional expertise is merely to add the expert evaluation as an additional factor in the statistical algorithm.

My problem with this is the framing as “human expert vs computer” by people who don’t really understand what computers do. Here’s my story:

In all of the cited cases, as is adequately explained by the article, computers don’t make up the models. What we’re seeing is not human knowledge replaced by computers but simply newly established human knowledge competing with “traditional” human knowledge.

Cheap computing power has made statistical analysis as a tool for testing and creating hypotheses much more competitive, and so it’s not very surprising to me that we see it gain an increasing mindshare over the more traditional “human” expertise. While the foundations are nothing new, the computerized way of infering and testing hypotheses on large datasets is increasingly able to beat the traditional “synthesize knowledge from what the regularities of your observations” way. However, the rules are still made by human experts – it’s just that the experts now use new tools and perform heavy computation.

The emotional component of this “dehumanizing mechanism” is just that there’s a component that is apparently mysterious to people who don’t know the mathematics and/or technology involved. To me, if someone is able to predict the quality of wine just by observing the amount of rainfall in the year of the harvest, that person is as much an expert as someone predicting it through a poorly understood process of extrapolation from the taste of an intermediate product. There is no dehumanization of the process just because the hypothesizer used a computer to create and test his model or because a computer is used to calculate the score.

The boundary of dehumanization is a bit unclear to me, but I’d say that what we’re currently facing are much more organizational threats than technological ones. For example, a credit score is something that is algorithmically created for a person and has a huge influence over their lives, but the details of the algorithm and its parameters are secret, so I can understand that it makes you feel powerless to grope in the dark and always have the fear of “blemishing your credit” over your head when considering something as innocent as cancelling a credit card you no longer want. Still, I assume there is still someone who actually knows how this thing works. The real boundary of dehumanization is probably reached when the system reaches a point of complexity where it’s not possible to come up with a verifiable justification for a certain input/ouput combination because there are so many tunables and cross-references in the system (come to think of it, I’m not convinced that that point hasn’t been reached in the credit-scoring system, yet). I don’t even think it takes “true” artificial intelligence to reach such a point, just a huge software system that grows until nobody really understands everything that went into it. I really enjoy the thought of executives dancing around a glowing mainframe that houses their ancient decision support system that always gives the right answer, but that nobody really understands. I just hope we can keep stuff like this out of our laws.

Update: Here’s Marginal Revolution on the author of the article (who apparently knows what he’s talking about – so I wonder why the article is framed like that?)

Why is it that I am a liberal rationalist, but like a) propaganda songs and b) sacred music so much?

Item (+MP3) (thanks, Gregor!):

Sie hat uns alles gegeben,

Sonne und Wind und sie geizte nie.

Wo sie war, war das Leben,

Was wir sind, sind wir durch sie.

Sie hat uns niemals verlassen,

Fror auch die Welt, uns war warm.

Uns schützt die Mutter der Massen,

Uns trägt ihr mächtiger Arm.

[...]

Item (MP3 sample):

Den Satan unter unsre Füße treten.

Erhör uns, lieber Herre Gott!

[...]

Und uns für des Türken und des Papsts

grausamen Mord und Lästerungen,

Wüten und Toben väterlich behüten.

Erhör uns, lieber Herre Gott!

Item (MP3 sample):

Mine eyes have seen the glory of the coming of the Lord:

He is trampling out the vintage where the grapes of wrath are stored;

He hath loosed the fateful lightning of His terrible swift sword:

His truth is marching on.



Glory, glory, hallelujah!

Glory, glory, hallelujah!

Glory, glory, hallelujah!

His truth is marching on.

I’d guess it is the longing for simple world where truth is clear cut. Of course, when parading through my living room singing the praise of the party or joining the choir to fend of the temptations of Satan, I know I’d feel deeply uncomfortable in the real-life environment where such songs “live”… It’s a bit of a conundrum, really.

PS: The Bach cantata is great music, of course. Still, I’d classify it more a case of the ideological fervor getting to me. For the music that Douglas Adams probably meant when he described Bach as ‘the music of life itself’ (or, more precisely, ‘the music copied by the guy who was played the music of life itself by a time-travelling guy’, but that’s in the book), I’d vote for BWV 1042.

Update:
Fixed the final link. Really, it’s amazing.

I just read the new Paul Graham essay, “Is It Worth Being Wise?”.

[...]And while wisdom yields calmness, intelligence much of the time leads to discontentment.

That’s particularly worth remembering. A physicist friend recently told me half his department was on Prozac. Perhaps if we acknowledge that some amount of frustration is inevitable in certain kinds of work, we can mitigate its effects. Perhaps we can box it up and put it away some of the time, instead of letting it flow together with everyday sadness to produce what seems an alarmingly large pool. At the very least, we can avoid being discontented about being discontented.

Good, I always feared that antidepressants would mess with mathematical ability too much. Maybe I should take up amphetamines?

The wisdom vs intelligence distinction overall is plausible, and I definitely agree with many of his observations (discipline hinders intelligence while furthering wisdom, for example). Still, the definition of wisdom as average outcomes over situation space and intelligence as the height of the peaks feels wrong to me. In this metric, I’d speculate that there’s a somewhat fixed area in the graph for each person and that the distributions that Paul calls “intelligent” and “wise” would then form through either specialization in a narrow domain of knowledge or a more general education.

Personally, I think of intelligence as the ability to form new knowledge. The choice for a person seeking optimal outcomes then becomes how to distribute effort between increasing intelligence and applying it to form and utilize knowledge (another distinction). That sounds like a pretty basic optimization problem, actually (given a known life time and a straightforward relation between effort spent building intelligence and intelligence gained). After this, the model starts to become convoluted as you start to consider knowledge retention rates and costs, contradictory information and various biology-related constraints. It’s an interesting question, but I fear it’s much to complicated to expect good popular literature on it anytime soon.

Somebody believes that physicists need to experiment. Thus, physicis students need to learn to experiment. To this end, they are subjected to lab courses where they have to re-enact various classical experiments and ideally reproduce their results. From the first lab – whose output consists of measuring values and writing them in pre-formatted tables – upwards, the work tends to become more indepent. This year’s major addition was the requirement to produce a written documentation of each experiment, which suddenly led to increased interest in scientific publishing on my part.

I’ve been known to rant about OpenOffice.org in the past, but like every serious ranter, I need to face up to the question: What else? At the beginning of this semester, I didn’t have a serious answer (which is why the first two documents were produced in OO.o), but by now I’m all set up. Here’s a couple of reasons you don’t want to use OpenOffice:

• The formula editor sucks. Formulas in continous text always look strange. There’s no way to use styles for formula objects. If you want to change the fonts in all your equations, you need to do so manually for each one.
• Graphics support sucks. oowriter does handle EPS files on Linux, but apparently, the EPS support doesn’t work on Windows. It is supposed to work with a PS printer driver installed, but I couldn’t reproduce that. It also can’t use PDFs as graphics on either platform, which is a mystery to me since that is pretty much the lingua franca in document snippet exchange these days. I ended up using GhostScript to convert my EPS graphics to 1200 dpi GIF files, but I refuse to call that a solution.
• Graphing support sucks. OpenOffice can’t fit curves except for simple linear functions. It doesn’t support math typesetting in graphs. Besides, the user interface of the Chart module is a major PITA.

Of course, in typical UNIX fashion, the solution isn’t just one tool, but a whole toolchain. Here’s a short overview of the tools involved:

1. gnuplot – awesome graphing capabilities
2. GNU Emacs – mostly for its Gnuplot interaction mode
3. LaTeX – typesetting
4. Vim – LaTeX editor of choice
5. GNU Make – tying things together
6. OpenOffice.org Calc – data entry and basic math
7. calc2latex – LaTeX table generation
8. Subversion – version control

Before or during the experiment, I set up an OpenOffice spreadsheet to enter the data, usually along with some preliminary calculations to catch entirely ridiculous results while there’s still time to check for errors. This is where the data goes during the experiment. Afterwards, I usually spend a some time cleaning this up and going through post-processing, mostly for error calculations and more complex evaluations. Once the values are deemed finished, those that will enter plots are exported to separate text files for gnuplot to read. I use gnuplot-mode in EMACS to interactively develop the plot until it looks good in the X11 terminal (I should talk about the absolute awesomeness of gnuplot here, but that’s for another post), then store the resulting gnuplot script in a foo.gnuplot file. Stuff that ends up in tables is exported as table environments to bar.tex files via calc2latex. Including either a plot or a table in the main LaTeX document then only reguires an \include{foo} or \include{bar} and an addition to the Makefile. Here’s a quick overview of the Makefile I usually use to compile my documents:


.PHONY: view all clean


These standard commands should be executed even when everything looks like it’s up to date.


tables = Nullpunkt.tex Abklingzeit-Tabelle.tex Motor.tex


This variable contains the list of the generated tables.


plots = Kalibrierkurve.gnuplot Seilspannung.gnuplot Abklingzeit.gnuplot Resonanzkurven.gnuplot Nullpunkt-Diagramm.gnuplot Nullpunkt2-Diagramm.gnuplot Phasenraum.gnuplot Phasenlage-1_25V.gnuplot Phasenlage-8V.gnuplot Phasenlage-15V.gnuplot Schwingung-0A.gnuplot Phasenraum2.gnuplot Schwebung1.gnuplot Schwebung2.gnuplot


This list contains the names of the gnuplot scripts that generate my plots.


gentex = $(plots:gnuplot=tex)<br/>
geneps = $(plots:gnuplot=eps)<br/>
figures = $(plots:gnuplot=pdf)<br/>


These variables then contain the list of the various intermediate files that gnuplot produces.


all: Protokoll-Pendel.pdf


The standard build result.


clean:<br/>
&nbsp;&nbsp;&nbsp;&nbsp;-rm *.pdf *.aux *.log *.eps $(gentex) $(geneps)


A crude clean target, to make that “make clean” remove all the generated files. Note the ‘-’ at the beginning that causes make to ignore errors.


Protokoll-Pendel.pdf: Protokoll-Pendel.tex $(figures) $(tables) <br/>
&nbsp;&nbsp;&nbsp;&nbsp;pdflatex $&lt; <br/>
&nbsp;&nbsp;&nbsp;&nbsp;pdflatex $&lt; <br/>
&nbsp;&nbsp;&nbsp;&nbsp;make view <br/>


This builds the main file twice (for references and the ToC) and displays it whenever one of the parts changes.


view:<br/>
&nbsp;&nbsp;&nbsp;&nbsp;xpdf Protokoll-Pendel.pdf &amp;


Display the result in xpdf.


%.pdf: %.eps<br/>
&nbsp;&nbsp;&nbsp;&nbsp;@echo "eps2pdf: $&lt; -> $@"<br/>
&nbsp;&nbsp;&nbsp;&nbsp;epstopdf $&lt; <br/>


General rule to convert the EPS graphics from gnuplot to PDFs needed by pdflatex. This isn’t necessary if you’re using normal LaTeX, but I hate DVIs, so I work with PDF directly.


%.eps: %.gnuplot<br/>
&nbsp;&nbsp;&nbsp;&nbsp;(<br/>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;echo set term epslatex color<br/>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;echo set out \"$(@)\" <br/>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;cat $&lt;<br/>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;echo set out<br/>
&nbsp;&nbsp;&nbsp;&nbsp;) | gnuplot -<br/>
&nbsp;&nbsp;&nbsp;&nbsp;perl -npe 's/\./,/g;' -i $(subst eps,tex,$@)<br/>


This is the rule that actually creates the plots. The first command wraps the interactive gnuplot script with the header and footer needed to generate an appropriate output file. The second command replaces the ‘.’ decimal separator in the generated TeX file with the comma that is appropriate in German documents.

With these few lines of magic in place, writing the actual document in Vim becomes rather comfortable. I use vim’s :make command to see the current state of the document whenever I feel like that, and it works nicely, no matter whether I’m editing a plot, a table or the main TeX source. It’s reasonably quick to a add a new plot or a new table, and document history is nicely traceable through svn.

What could be better in the current workflow?

• Modelling. The part that is still dominated by OpenOffice Calc is cumbersome and inelegant. Entering a slightly complex formula is complicated and error-prone since there is no symbolic notation – a typical cell formula looks something like this: =0.0000004*PI()*$A12*$B$3/$B$5*(($B$4/2+$B$5)/SQRT($B$6^2+($B$4/2+$B$5)^2) - $B$4/2/SQRT($B$6^2+($B$4/2)^2)). That would be a lot nicer if there was a way to give names to cells in Calc. I’ve been hoping to find a clever way to do this in Maple, but I haven’t yet figured out how to do it.
• Table export. While calc2latex is really a highly useful package, I still do a lot of manual postprocessing on the generated files until the formatting looks good. This is a major timesink that I need to get rid of. Probable routes include hacking calc2latex to automatically consider my formatting preferences, learning enough TeX to make a custom table environment that fits my wishes or writing a postprocessor to automate the changes.
• Makefile maintenance. Keeping track of plots and tables is not too much work, but in principle it should well be possible to just scan the main TeX file and automagically find out what its dependencies are. Something like gcc -M would be truly elegant.
• Plot Data. Currently, changes in the datafiles that the plots reference do not trigger regeneration of the plots. Another automatic dependency scanner, I guess.

As always, comments and suggestions are welcome!

What good are university grades? I’ve been pondering and discussing this for some time.
My strategy back in school didn’t really have a rational background. I suppose classes somehow ended up in one of three categories. “Interesting” classes were worthy of active participation (resulting in the top grade most of the time), “don’t care” classes didn’t receive any active consideration (top grade or second best), and a number “crap” classes served as my personality quirk outlet where I’d screw up my grade by simply refusing to do assignments or participate in prescribed activities. At the end of the year, this always placed me near, but AFAIK never at, the top of my class. While I’ve nowadays come to see my old behaviour pattern as rather immature and would like to think that maybe some of my school time could have been better spent if there’d been some more advanced stuff to do for the students who were bored in the actual classes, I actually had a really good time during these five years. Since I was really fascinated with my area of specialization, I actually used a lot of my free time to improve upon my skills and learn interesting stuff, even though my schedule contained a daily afternoon nap (between the end of The Simpsons and the end of Baywatch) and a spectacular amount of drinking and other similarly important activity.

In university, the situation has changed slightly. Because I was worried that I wouldn’t make it at all, I spent semester one working really hard and seeing how well I can do. Since the results were near-perfect, I now face the same old decision: Strive for grades or have a good time? To further set up the question, here’s two contrasting quotes:

If you decide you don’t have to get A’s, you can learn an enormous amount in college.
I. I. Rabi, physics Nobel laureate

Never underestimate how big a deal your GPA is. Lots and lots of recruiters and hiring managers, myself included, go straight to the GPA when they scan a resume, and we’re not going to apologize for it. Why? Because the GPA, more than any other one number, reflects the sum of what dozens of professors over a long period of time in many different situations think about your work. SAT scores? Ha! That’s one test over a few hours. The GPA reflects hundreds of papers and midterms and classroom participations over four years.

Joel Spolsky, software entrepreneur

Of course, the first thing to note is that these people probably have different goals in mind. I don’t have context for Rabi’s quote (I came across it in the opening chapter of My Life as a Quant), but the Joel quote is from an essay aimed at CS students looking to optimize their employability. I suspect that Rabi’s quote is from a quite different background, the mystery-shrouded world of exceptional scientists. At least as far as their biographies go, these people seem to be driven by an exceptional curiosity about the world. I’m mildly curious, myself, but that’s one of the things I see suffering when I’m working on grades. Perhaps it’s a good indicator that I never once felt like doing anything physics or mathematics related that I hadn’t been assigned for my coursework since the start of this semester. When I look at my current university life, I feel like an unhappy kid in school, wishing for every lecture to end sooner rather than later and constantly worried about not keeping my test scores in the top group. The only consolation I have is looking back at the enormous amount of things I have learned in the past seven months. Still, I keep asking myself whether this is the way an education is supposed to run – I keep pushing myself to do work I grow to hate progressively more, and at the end, I miraculously discover that I’d now like to do research in that area? It feels wrong.

So, I’m currently toying with the idea of loosening the focus on grades for the second year of university. Here’s an outline of my calculation:

Gains

• Time – there’s an insane amount of work going into the difference between 70%-80% scores and 95% scores, and from then on, it gets harder. Returns seem to be diminishing.
• Peace of Mind – I’ll probably be happier in a less closely metered situation where I can actually justify spending a weekend without any work on university stuff. Maybe I’ll even have enough energy left to actually work on interesting side projects.

Risks

• Money – I hear that there’s grant money available for people who do really well. However, the sums I keep hearing about are paltry, something like two weeks’ worth of work, and competition is intense. I don’t think this one worries me much.
• Laziness – While my current work regime breeds discontent, I do seem to absorb a lot of knowledge that way. I’d like to experiment a bit more with learning on my own, but I’m not quite sure how effective this is going to be. I see this as the biggest danger to the whole plan since it’s rather easy to let my effort levels be guided by outer pressure. Dragging my tired body to every single lecture and doing every problem that I’m assigned is a lot easier than independently assessing that a) I really understand what I’m doing and b) that I’m actually doing as much work as I should. Good ideas on independently packaging large chunks of work like “all of electrodynamics”?
• Signalling – Who will care about my grades? Obviously, grades are somewhat of a signal when aiming for an academic career. The question here is how a curmudgeonly A student does against an enthusiastic B+ student with some ideas that were not picked up from the standard presentation delivered in the lecture. I have no idea. Then, what about the fun parts, like summer schools or visiting semesters abroad? The other people who might care for grades are future employers. Can anyone who graduated in Europe tell me just how important their grades were in this respect?

There’s still a lot of uncertainty left here, but at the moment I figure I just need to give it a try. Sage advice is, of course, welcome. Have you tried and failed? Become a happy slave of the grade machine? Succeeded in having a good time in unversity and still learned a lot?